Approaches for Automated Object Recognition and Extraction from Images — a Study

Abstract

Digital Image Interpretation is one of the most challenging and important tasks in many scientific and engineering applications. The two vital subtasks in image interpretation are recognition and extraction of object(s) of interest (OOI) from an image. When such tasks are manually performed, it calls for human experts, making them more time consuming, less cost effective and highly constrained. These negative factors led to the development of a computer system which performed an automatic analysis of visual information in order to bring in consistency, efficiency and accuracy in image analysis. This paper focuses on the survey of various existing automated approaches for recognition and extraction of OOI from an image in various scientific and engineering applications. In this work a categorization of these approaches is made based on the four principle factors (Input, Object, Feature, Attention) with which each approach is driven. Most of the approaches discussed in this paper are proved to work efficiently in real environments.